{"title":"挑战与机遇:从近内存计算到内存计算","authors":"Soroosh Khoram, Yue Zha, Jialiang Zhang, J. Li","doi":"10.1145/3036669.3038242","DOIUrl":null,"url":null,"abstract":"The confluence of the recent advances in technology and the ever-growing demand for large-scale data analytics created a renewed interest in a decades-old concept, processing-in-memory (PIM). PIM, in general, may cover a very wide spectrum of compute capabilities embedded in close proximity to or even inside the memory array. In this paper, we present an initial taxonomy for dividing PIM into two broad categories: 1) Near-memory processing and 2) In-memory processing. This paper highlights some interesting work in each category and provides insights into the challenges and possible future directions.","PeriodicalId":269197,"journal":{"name":"Proceedings of the 2017 ACM on International Symposium on Physical Design","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2017-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"27","resultStr":"{\"title\":\"Challenges and Opportunities: From Near-memory Computing to In-memory Computing\",\"authors\":\"Soroosh Khoram, Yue Zha, Jialiang Zhang, J. Li\",\"doi\":\"10.1145/3036669.3038242\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The confluence of the recent advances in technology and the ever-growing demand for large-scale data analytics created a renewed interest in a decades-old concept, processing-in-memory (PIM). PIM, in general, may cover a very wide spectrum of compute capabilities embedded in close proximity to or even inside the memory array. In this paper, we present an initial taxonomy for dividing PIM into two broad categories: 1) Near-memory processing and 2) In-memory processing. This paper highlights some interesting work in each category and provides insights into the challenges and possible future directions.\",\"PeriodicalId\":269197,\"journal\":{\"name\":\"Proceedings of the 2017 ACM on International Symposium on Physical Design\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-03-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"27\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 2017 ACM on International Symposium on Physical Design\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3036669.3038242\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 2017 ACM on International Symposium on Physical Design","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3036669.3038242","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Challenges and Opportunities: From Near-memory Computing to In-memory Computing
The confluence of the recent advances in technology and the ever-growing demand for large-scale data analytics created a renewed interest in a decades-old concept, processing-in-memory (PIM). PIM, in general, may cover a very wide spectrum of compute capabilities embedded in close proximity to or even inside the memory array. In this paper, we present an initial taxonomy for dividing PIM into two broad categories: 1) Near-memory processing and 2) In-memory processing. This paper highlights some interesting work in each category and provides insights into the challenges and possible future directions.